Breast Cancer Classification from Mammogram Images Using Extreme Learning Machine-Based DenseNet121 Model

Table 6

Performance measure results of the models with batch size 128.

Models	No. of iteration	Specificity	Sensitivity	Training accuracy	Testing accuracy	Computational time in minutes
VGG19	100	97.73	97.98	97.76	97.88	211.2344
MobileNet	100	98.53	98.41	98.23	98.42	198.1212
Xception	100	98.65	98.82	98.85	98.73	194.2076
ResNet50V2	100	98.56	98.87	98.76	98.37	193.1878
InceptionV3	100	100	99.52	98.63	98.52	183.1881
InceptionResNetV2	100	98.59	100	98.58	98.47	167.1242
DenseNet201	100	98.84	99.28	98.98	98.85	164.3344
DenseNet121	100	99.18	100	99.27	98.84	160.4033
DenseNet121+ELM	100	99.37	99.94	99.47	99.14	159.7731